Processing of Dispersive Waves in Acoustic Logging
Methods and systems for displaying sonic logging data are described herein. The displayed data includes highly reliable quality control (QC) indicators that can be used to identify any need for a dispersion correction. The disclosed data-driven approach determines whether a dispersion curve is asymptotic to the true formation shear slowness by calculating a coherence of the slowness at frequency intervals of the dispersion curve to indicate the level of the velocity dispersion. This coherence indicator can then be plotted against the averaged slowness within the frequency interval to show how well the asymptotic slowness is approached. The coherence indicator can be projected onto a slowness log as a QC indicator. A calculated formation shear slowness can be overlaid upon the slowness log.
1 . A method of displaying sonic logging data associated with an earth formation traversed by a borehole, the method comprising:
acquiring sonic data at a plurality of depths in the borehole using a receiver array,
processing the acquired sonic data to generate a slowness-versus-depth log,
processing the acquired sonic data at each of the plurality of depths to generate a dispersion plot of slowness-versus-frequency for each depth,
determining an asymptotic index (A.I.) for each of the dispersion plots, wherein the A.I. indicates an extent to which the dispersion plot asymptotically approaches a formation slowness,
projecting the determined A.I.s onto the slowness-depth log, and
displaying the slowness-versus-depth log, wherein the projection of the A.I.s comprises a plurality of color bands corresponding to the determined A.I.s.
2 . The method of claim 1 , wherein determining an A.I. for each of the dispersion plots comprises:
segmenting the dispersion plot into a plurality of frequency windows, and
for each frequency window, determining a mean slowness and a standard deviation of slowness values within the window.
3 . The method of claim 2 , wherein the asymptotic index A.I. is defined as:
A
.
I
.
=
1
-
SD
S
m
where SD is the standard deviation of the slowness within the frequency window and S m is the mean slowness within the frequency window.
4 . The method of claim 1 , wherein the formation slowness is a shear slowness, compressional slowness, or Stoneley slowness.
5 . The method of claim 1 , wherein determining an A.I. for each of the dispersion plots comprises:
segmenting the dispersion plot into a plurality of frequency windows, and
for each frequency window, determining a mean slowness, the maximum slowness, and the minimum slowness values within the frequency window.
6 . The method of claim 1 , wherein determining an A.I. for each of the dispersion plots comprises:
segmenting the dispersion plot into a plurality of frequency windows, and
for each frequency window, determining a mean slowness, a slowness value at a low-frequency edge of the window, and a slowness value at a high-frequency edge of the frequency window.
7 . The method of claim 1 , wherein determining an A.I. for each of the dispersion plots comprises:
segmenting the dispersion plot into a plurality of frequency windows, and
determining a sub-A.I. value for each frequency window,
segmenting the dispersion plot into a plurality of slowness windows, and
determining an A.I. value for each slowness windows by summing the sub-A.I. values within each of the plurality of slowness windows.
8 . The method of claim 7 , wherein determining a sub-A.I. value for each frequency window comprises: determining a mean slowness and a standard deviation of slowness values within the window.
9 . The method of claim 8 , wherein the sub-A.I. value is defined as:
subA
.
I
.
=
1
-
SD
S
m
where SD is the standard deviation of the slowness within the frequency window and S m is the mean slowness within the frequency window.
10 . The method of claim 7 , further comprising determining a histogram of total sub-A.I. values as a function of slowness.
11 . The method of claim 1 , further comprising:
determining a wave slowness of the formation at the plurality of depths, and overlaying a plot of the determined wave slowness on the displayed slowness-versus-depth log.
12 . A non-transitory computer readable medium comprising instructions, which, when executed on a computing device, configure the computing device to:
access data comprising sonic data acquired at a plurality of depths in the borehole using a receiver array,
process the acquired sonic data to generate a slowness-versus-depth log,
process the acquired sonic data at each of the plurality of depths to generate a dispersion plot of slowness-versus-frequency for each depth,
determine an asymptotic index (A.I.) for each of the dispersion plots, wherein the A.I. indicates an extent to which the dispersion plot asymptotically approaches formation slowness,
project the determined A.I.s onto the slowness-depth log, and
display the slowness-versus-depth log, wherein the projection of the A.I.s comprises a plurality of color bands corresponding to the determined A.I.s.
13 . The non-transitory computer readable medium of claim 12 , wherein determining an A.I. for each of the dispersion plots comprises:
segmenting the dispersion plot into a plurality of frequency windows, and
for each frequency window, determining a mean slowness and a standard deviation of slowness values within the window.
14 . The non-transitory computer readable medium of claim 13 , wherein the asymptotic index A.I. is defined as:
A
.
I
.
=
1
-
SD
S
m
where SD is the standard deviation of the slowness within the frequency window and S m is the mean slowness within the frequency window.
15 . The non-transitory computer readable medium of claim 12 , wherein the instructions further configure the computing device to:
determine a wave slowness of the formation at the plurality of depths, and
overlay a plot of the determined wave slowness on the displayed slowness-versus-depth log.
16 . The non-transitory computer readable medium of claim 12 , wherein the formation slowness is a shear slowness, compressional slowness, or Stoneley slowness.
17 . A system comprising:
a receiver array deployable in a borehole traversing an earth formation,
a computing device, and
a non-transitory computer readable medium comprising instructions, which, when executed on a computing device, configure the computing device to:
access sonic data acquired at a plurality of depths in the borehole using the receiver array,
process the acquired sonic data to generate a slowness-versus-depth log,
process the acquired sonic data at each of the plurality of depths to generate a dispersion plot of slowness-versus-frequency for each depth,
determine an asymptotic index (A.I.) for each of the dispersion plots, wherein the A.I. indicates an extent to which the dispersion plot asymptotically approaches formation shear slowness,
project the determined A.I.s onto the slowness-depth log, and
display the slowness-versus-depth log, wherein the projection of the A.I.s comprises a plurality of color bands corresponding to the determined A.I.s.
18 . The system of claim 17 , wherein determining an A.I. for each of the dispersion plots comprises:
segmenting the dispersion plot into a plurality of frequency windows, and
for each frequency window, determining a mean slowness and a standard deviation of slowness values within the window.
19 . The system of claim 18 , wherein the asymptotic index A.I. is defined as:
A
.
I
.
=
1
-
SD
S
m
where SD is the standard deviation of the slowness within the frequency window and S m is the mean slowness within the frequency window.
20 . The system of claim 17 , wherein the formation slowness is a shear slowness, compressional slowness, or Stoneley slowness.